System and method for auto-focusing in optical coherence tomography

ABSTRACT

A system, in one embodiment, includes an optical coherence tomography (OCT) imaging system having a light source configured to emit light. The OCT imaging system further includes a beam splitter configured to receive the light from the light source, split the light into a first light portion directed along a sample arm comprising a sample and a second light portion directed along a reference arm comprising a reference mirror, receive a first reflected light portion from the sample arm and a second reflected light portion from the reference arm, combine the first and second reflected light portions to obtain an interference signal at a detector. Further, the OCT imaging system includes a controller having logic configured to perform an auto-focusing process to determine the optimal position for a lens in the sample arm in order to bring the sample into focus.

BACKGROUND OF THE INVENTION

Embodiments of the present invention relate to systems, methods, anddevices for imaging and, more particularly, to optical coherencetomography (OCT) imaging techniques.

Optical coherence tomography (OCT) is a non-invasive imaging techniquethat is often used in clinical applications to obtain high-resolutioncross-sectional images of subsurface in vivo (living) biological tissueand other materials. For example, OCT imaging techniques are used in avariety of medical fields, including ophthalmology, cardiology, anddermatology, to name just a few. In particular, OCT imaging is popularin ophthalmology for ocular diagnostic purposes, where it may be used toobtain detailed images of a retina or other structures within a humaneye. For instance, OCT imaging has been known to be capable ofdelineating layers of the retina with a very high degree of clarity.Currently, some OCT imaging techniques are capable of producing imagesat micrometer, or even sub-micrometer, scale resolutions.

OCT imaging systems operate on the principle of interferometry, in whichsubsurface light reflections are resolved to provide a tomographicvisualization of a sample (e.g., the tissue or object being imaged).Generally, OCT imaging systems split light provided by a light sourcealong a first optical path containing the sample, usually referred to asa “sample arm,” and a second optical path containing a reference mirror,usually referred to as a “reference arm.” The combination of reflectedlight from the sample arm and reflected reference light from thereference arm gives rise to an interference pattern, but generally onlyif light from both arms have traveled the “same” optical distance,wherein “same” means a difference of less than a coherence length. Thus,when acquiring images using an OCT imaging system, an operator may betasked with ensuring that the reference and sample arms have the samepath length, which may involve adjusting the length of the reference armmanually, so that an interference pattern is properly generated. As canbe appreciated, due to variations in the size or dimensions of aparticular sample type, such as human eyes, the path length of thesample arm may vary, thus requiring the path length of the reference armto vary to match the sample arm. Moreover, because the path lengths areto be adjusted until they match (e.g., typically with a tolerance of afew millimeters, or even micrometers), this task may not only bedifficult to perform accurately, but may also be subject to human error.

Further, once the reference and sample arms are matched, the operatormay also be tasked with manually adjusting the focal position of one ormore focusing lenses of the OCT system to ensure that the acquired imageis in focus. As can be appreciated, manually determining an optimalfocusing position may be difficult, particularly when such adjustmentsare sometimes on the order of micrometers (μm). Moreover, since thefocus quality of such adjustments may be subjectively determined basedon an operator's vision, what is perceived to be an optimal focusposition for the lens may not always correspond to what is actually theoptimal focus position. Accordingly, there exists a need for an OCTimaging system that is capable of automating the manual tasks discussedabove, thus removing the labor-intensive aspects of OCT imaging whileimproving the performance and accuracy of OCT imaging systems.

BRIEF DESCRIPTION OF THE INVENTION

Certain embodiments commensurate in scope with the originally claimedinvention are summarized below. These embodiments are not intended tolimit the scope of the claimed invention, but rather these embodimentsare intended only to provide a brief summary of possible forms of theinvention. Indeed, the invention may encompass a variety of forms thatmay be similar to or different from the embodiments set forth below.

In one embodiment, an optical coherence tomography (OCT) imaging systemincludes a light source configured to emit light. The OCT imaging systemalso includes a beam splitter configured to receive the light from thelight source, split the light into a first light portion directed alonga sample arm comprising a sample and a second light portion directedalong a reference arm comprising a reference mirror, receive a firstreflected light portion from the sample arm and a second reflected lightportion from the reference arm, combine the first and second reflectedlight portions to obtain an interference signal at a detector. Further,the OCT imaging system includes a controller having logic configured toperform an auto-focusing process to determine an optimal focal positionfor a lens in the sample arm in order to bring the sample into focus.

In another embodiment, a method for focusing a sample in a sample arm ofan optical coherence tomography (OCT) imaging system includes acquiringan image of the sample through a focusing lens at each of a plurality offocal points along a focal range in the sample arm. The method furtherincludes determining a figure of merit data point for each acquiredimage, using the figure of merit data points to determine a mathematicalfunction defining a curve fitted to the figure of merit data points, andusing the curve to determine an optimal focal position. Finally, themethod includes using a lens position control device to adjust thefocusing lens to the optimal focal position.

In yet a further embodiment, a tangible computer-readable medium havinginstructions encoded thereon includes code configured to cause afocusing lens in a sample arm of an optical coherence tomography (OCT)imaging system to be positioned at each of a plurality of discrete focalpoints along a focal range in the sample arm. The tangiblecomputer-readable medium also includes code for acquiring an image of asample in the sample arm at each of the focal points, code forcalculating a figure of merit value from each of the images, code forfitting a mathematical function to the figure of merit values, and codefor determining an optimal focal position based on the mathematicalfunction. Finally, the tangible computer-readable medium includes codeto cause the focusing lens to be adjusted based upon the optimal focalposition.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presentinvention will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 is a schematic block diagram depicting an optical coherencetomography (OCT) imaging system including a controller configured toprovide for auto-ranging and/or auto-focusing functions, in accordancewith an embodiment of the present invention;

FIG. 2 is a block diagram illustrating the controller of FIG. 1 in moredetail, in accordance with an embodiment of the present invention;

FIG. 3 illustrates a composite scan that may be determined during anauto-ranging process, in accordance with an embodiment of the presentinvention;

FIG. 4 is a flow chart depicting a process for auto-ranging to match areference arm with a sample arm, in accordance with an embodiment of thepresent invention;

FIG. 5 is a more detailed view showing how a focusing lens within thesample arm may be adjusted, in accordance with an embodiment of thepresent invention;

FIGS. 6A-6I illustrate images of a sample that may be obtained atvarious focal positions during an auto-focusing process, in accordancewith an embodiment of the present invention;

FIG. 7 is a graph depicting several examples of figures of merit (FOMs)that may be used to determine an optimal focal position for a lens in asample arm of an OCT imaging system, in accordance with an embodiment ofthe present invention;

FIG. 8 is a graph illustrating the use of an FOM that includes theinverse of a Brenner gradient, in accordance with an embodiment of thepresent invention; and

FIG. 9 is a flow chart depicting a process for auto-focusing, inaccordance with an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

One or more specific embodiments of the present invention are describedbelow. In an effort to provide a concise description of theseembodiments, all features of an actual implementation may not bedescribed in the specification. It should be appreciated that in thedevelopment of any such actual implementation, as in any engineering ordesign project, numerous implementation-specific decisions must be madeto achieve the developers' specific goals, such as compliance withsystem-related and business-related constraints, which may vary from oneimplementation to another. Moreover, it should be appreciated that sucha development effort might be complex and time consuming, but wouldnevertheless be a routine undertaking of design, fabrication, andmanufacture for those of ordinary skill having the benefit of thisdisclosure.

When introducing elements of various embodiments of the presentinvention, the articles “a,” “an,” “the,” and “said” are intended tomean that there are one or more of the elements. The terms “comprising,”“including,” and “having” are intended to be inclusive and mean thatthere may be additional elements other than the listed elements.

As discussed in detail below, embodiments of the present inventionrelate to techniques for auto-ranging and auto-focusing in the contextof optical coherence tomography imaging. To facilitate a betterunderstanding, the present application is partitioned into threesections, namely a first section that provides a general overview of anoptical coherence tomography imaging system, a second section thatdescribes auto-ranging techniques, and a third section that describesauto-focusing techniques.

I. Optical Coherence Tomography Overview

With the foregoing points in mind, FIG. 1 is a schematic block diagramdepicting an optical coherence tomography (OCT) imaging system 10, inaccordance with embodiments of the present invention. Particularly, aswill be discussed in further detail below, the OCT imaging system 10 maybe configured to perform auto-ranging to match a reference arm with asample arm and/or auto-focusing to adjust a focusing lens in the samplearm to an optimal focal position.

As noted above, OCT is an imaging technique that operates based on theprinciple of interferometry, wherein light reflections from a sample anda reference point are resolved to generate an interference pattern thatmay be used to obtain a tomographic visualization of the sample, such asbiological tissue. For example, OCT imaging systems, such as the system10, may split light provided by a light source to a sample arm and areference arm. The reflected light from the sample and the reflectedlight from the reference, which may be a mirror, are combined orsuperimposed to obtain an interference pattern. OCT imaging is bothpopular and useful, particularly in the field of ophthalmology andocular diagnosis, as the imaging techniques allows for non-invasiveimaging of sub-surface tissue, such as the retina of a human eye.Indeed, OCT imaging has been key in the early detection of certainocular ailments, such as diabetic retinopathy and macular degeneration.

As shown in FIG. 1, the OCT imaging system 10 includes a light source 12that may provide light 14 along a pathway 16 to a beam splitter 18. Byway of example, the light source 12 may be a broadband light source,such as a super-luminescent diode (SLD), mode-locked laser (e.g., aTiAl₂O₃ mode-locked laser), or an edge emitting LED. In one embodiment,the light source 12 may be configured to emit near-infrared light (e.g.,having a wavelength (λ) of between approximately 800 to 1000nanometers). The pathway 16 may be made of material configured totransmit light, such as an optical fiber.

The beam splitter 18 may be configured to split the light 14 into twoportions, referred to in FIG. 1 as light portion 20 and light portion22. In certain embodiments, the beam splitter 18 may be aninterferometer, such as a Michelson interferometer. Light portion 20 maybe guided along pathway 24 through a lens 28 to a sample 30, which is atarget that is being imaged. For instance, in a medical imagingapplication, the sample 30 may be organic tissue, such as a human eye.In other applications, such as art conservation applications the sample30 may also be an inorganic object (e.g., layers of a painting). Asindicated in FIG. 1, the path along which light portion 20 istransmitted may be referred to as the sample arm 32. The light portion22 is similarly guided along pathway 26 through another lens 36 to areference mirror, represented here by reference number 38, which maycollectively form the reference arm 40. As can be appreciated, thepathways 24 and 26, like the pathway 16, may also include optical fibersconfigured to transmit light.

As further shown in FIG. 1, the light portion 22 is reflected from thereference mirror 38 to form light portion 42, and the light portion 20is reflected from the sample 30 to form light portion 34. Light portion42 and light portion 34 are guided back to the beam splitter 18 by thepathways 26 and 24, respectively. The beam splitter 18 may combine thereflected light portions 34 and 42 to form the superimposed light beam44, which may represent an interference signal. As can be appreciated,most of the light 20 directed at the sample 30 scatters, which typicallyleaves only a small portion reflecting from sub-surface features ofinterest. Based on the principle of optical coherence, only thereflected (e.g., non-scattered) light is coherent and detected by thebeam splitter 18. Further, as will be appreciated, the scattered light,which may normally contribute to glare, may be filtered out. Forexample, a beam splitter, such as an interferometer, may be configuredto detect only coherent light.

The interference signal 44 may be guided to a spectrometer 46 by thepathway 43 (e.g., an optical fiber), and then be analyzed by thespectrometer 46 and the image capture device 47 to determine depth andopacity information. For instance, the interference signal 44 may bespectrally dispersed by the spectrometer 46 into spatially separatelight portions according to different wavelength ranges. These separatedlight portions may be detected by the image capture device 47, which mayinclude a charge-coupled device (CCD) or CMOS sensor with multiplepixels, a line scanning camera, or a combination thereof, to detect theintensities represented by each separate light portion. This data maythen be provided to the controller 48, which may apply one or moredigital signal processing steps to computationally translate the datainto a viewable image for viewing on the display 59. The process mayinvolve receiving and processing the intensity information to derivedepth information using Fourier transformations of the spectrarepresenting the separated light portions, as determined by thespectrometer 46. For example, the interference signal may be detected inthe spectral domain, and then inverse Fourier transformed to the timedomain, which may result in a signal that provides sample reflectivityas a function of depth. This type of optical coherence tomographyimaging may be referred to spectral domain OCT (SD-OCT) or Fourierdomain OCT. When compared to other OCT techniques, such as time-domainOCT, spectral domain OCT generally allows for higher resolution images,higher scan rates, and improved signal-to-noise ratio. However, itshould be appreciated, that the techniques related to auto-focusing andauto-ranging, as discussed below, may be applied to either of these OCTtechniques. In a further embodiment, spectral domain OCT imaging may beimplemented by using a narrow band light source in which the frequencyis swept rapidly in time across a broad tuning range, with theinterference signal being collected at each frequency while the sweptsource is tuned.

As discussed above, in order to properly measure the interferencebetween the light 34 reflected from the sample 30 and the light 42reflected from the reference mirror 38, the path lengths of the samplearm 32 and the reference arm 40 should be matched such that anydifference between the path lengths is less than a coherence length. Byway of example, if a typical OCT imaging system is configured to capturean image across a 2 to 3 millimeters of depth (e.g., a “minimum depth”),the path length of the sample arm 32 and the reference arm 40 much matchto within this distance. Moreover, variations in the sample 30 may addadditional uncertainty to the sample position. For instance, if thesample is a human eye, the human eye may, on average, have an axiallength that varies from between 22 to 30 millimeters, which adds adegree of uncertainly of 8 millimeters. Further, depending on thecharacteristics of a patient's head and/or face, as well as how thepatient is positioned, additional uncertainty may exist. For instance,these factors may inject up to another 10 millimeters of uncertainty.Thus, in light of this potential large range of uncertainty, it may bedifficult for conventional OCT imaging systems to locate where, in theaxial direction, the minimum depth (e.g., a 2-3 millimeter range) inwhich the sample 30 resides.

To address these issues, the controller 48 of the OCT imaging system 10of FIG. 1 may be configured to implement an auto-ranging function toautomatically match the path length of the reference arm 40 to that ofthe sample arm 32. As discussed in more detail below, the OCT imagingsystem 10 includes a mechanism 52 for adjusting the path length of thereference arm 40. For instance, the mechanism 52 may be mechanical innature, such as one or more rapid scanning optical delay (RSOD) lines.This allows for the length of the reference arm 40 to be adjusted indiscrete steps, wherein an axial scan may be acquired at each step alonga range of the total adjustment length to construct a composite longdepth range scan. For each discrete reference arm position, thecorresponding scan is analyzed to determine one or more figures of merit(FOM), with the controller 48 searching for the position in which theFOM is at a maximum (or a minimum depending on the metric being used).Once the correct position (e.g., one that matches the sample arm) isfound, the controller 48 provides the signal 50 indicating the correctposition to the reference arm control mechanism 52. The controlmechanism may then output the control signal 54, which may cause thereference arm to be adjusted to the selected position indicated by thesignal 50. In one embodiment, the control mechanism may include a servocontrol. This process will be discussed in more detail below in SectionII. In some embodiments, the adjustment of the reference arm to vary thepath length may include an angular adjustment, such as to the referencemirror 38. The magnitude of each discrete step may be equal or unequal.

Next, once the reference arm has been adjusted to the position selectedby the controller 48 in response to the auto-ranging function, thesample 30 may still need to be focused by adjusting the position of thelens 28 to an optimal focal position. Accordingly, the controller 48 ofthe present embodiment may also be configured to implement anauto-focusing function. As discussed in more detail below, the OCTimaging system 10 includes a lens position control mechanism 60 that maybe configured to adjust the focal position of the lens 28. To determinethe focal plane of the sample 30, the controller 48 may acquire an OCTimage at each of various focal positions of the lens 28. Each image maythen be analyzed by the controller 48 to determine one or morequantitative FOMs at each depth position. A model is then mathematicallyfitted to the FOM data, wherein the point corresponding to either aminimum or maximum (depending on the FOM used) corresponds to theoptimal focal position. Once the optimal focal position is found, thecontroller 48 provides the signal 58 indicating the focal position tothe lens control mechanism 60. Based on the signal 58, the lens controlmechanism 60 may output the control signal 62, which may cause the lens28 to be adjusted to the focal position indicated by the signal 58. Inone embodiment, the control mechanism 60 may include a motorizedactuation system. This auto-focusing process will be discussed in moredetail below in Section III.

FIG. 2 is a block diagram depicting a more detailed view of thecontroller 48, in accordance with an embodiment of the presentinvention. The functional blocks depicted in FIG. 2 may include hardwareelements (e.g., circuitry), software elements (e.g., computer codestored on computer-readable media, such as a hard drive or systemmemory), or a combination of both hardware and software elements. Asshown, the controller 48 may include a processor 63, memory device 64,and video output interface 66.

The processor 63 may generally be configured to control the functions ofthe controller 48, and thus of the OCT imaging system 10. For instance,the processor 63 may provide the processing capability to analyze andprocess the data captured by the image capture device 47, referred toherein by reference number 70. For example, as discussed above, theinterference signal 44 may be detected in the spectral domain, and theninverse Fourier transformed to the time domain, which may result in asignal that provides sample reflectivity as a function of depth. Theprocessor 63 may thus be configured to apply such transformationsbetween the spectral and time domains in order to extract depth andintensity information in order to generate viewable OCT images. The OCTimage(s) may be stored in the memory device 64 and/or sent to thedisplay 59 (FIG. 1) by way of the video output interface 66 as imagedata 68. For example, the interface 66 may include any suitable type ofdisplay interface, such as a VGA, DVI, HDMI, or DisplayPort interface.The display 59 may be any type of display suitable for displaying acomputer image, such as a cathode-ray tube (CRT) display, an LCDdisplay, or an organic LED (OLED) display. In some embodiments, theprocessor 63 may also be configured to provide post-processing functionson the digital OCT images, such as to enhance them for aestheticpurposes to potentially enable a medical professional to more easilyreview and reach a diagnosis. By way of example only, suchpost-processing functions may include noise reduction/removal,brightness/contrast adjustments, sharpening, and so forth.

The processor 63 may also be configured to operate in conjunction withthe auto-range logic 72 and the auto-focus logic 74 to provide theabove-mentioned auto-ranging and auto-focusing functions, as will bediscussed further below. In the illustrated embodiment, the processor 63may include one or more microprocessors, such as one or moregeneral-purpose microprocessors, application-specific microprocessors(ASICs), digital signal processors, or a combination of such processingcomponents.

The memory device 64 may include volatile memory, such as random accessmemory (RAM), or non-volatile memory, such as read-only memory (ROM),hard disk drive, or flash memory, or a combination of RAM and ROMdevices. For example, the memory device 64 may store OCT imagesgenerated by the processor 63, which may be stored for later viewing.Though not shown in FIG. 2, in some embodiments, the controller 48 mayinclude communication circuitry, such as a networking interface,enabling the controller 48 to send OCT image data to other devices. Forinstance, in such embodiments, OCT images acquired by the system 10 maybe sent to other devices for storage, such as a patient database system,such as a picture archive and communication system (PACS), or may besent to other devices for diagnostic purposes. The memory 64 also storesinstructions or data to be processed by the processor 63, which mayinclude instructions for processing the data 70, and for performingauto-ranging or auto-focusing functions. Further, when performingauto-ranging and/or auto-focus functions, the acquired images on whichFOMs are determined may be stored in the memory device 64.

II. Auto-Ranging Techniques

As discussed above, natural variations in a particular type of sample30, such as the human eye, may make it challenging to locate theposition of the sample 30 in order to match the reference arm 40 withthe sample arm 32. By way of example only, a human eye may have an axiallength that varies from between 22 to 30 millimeters, which adds adegree of uncertainly of approximately 8 millimeters. Thus, if it is theretina of the eye that is to be imaged, there may be an 8 millimeterwindow of uncertainty. That is, the retina of the eye is likely locatedsomewhere within that window. Further, based on variations in apatient's facial structure and/or how the patient positions their head,additional uncertainty, i.e., up to an additional 10 millimeters, may bepresent. For instance, using these example values, there may be an 18millimeter window of uncertainty in which the sample 30, i.e., thepatient's eye, is located in the sample arm 32. In some embodiments, thewindow of uncertainty may be between approximately 5 to 30 millimeters.Since the reference arm 40 and the sample arm 32 should be matched inorder to properly measure the interference between the reflected lightportions 34 and 42, the controller 48 may initially perform theauto-ranging function described above to determine the position of thesample 30 and to adjust the reference arm 40 accordingly.

To implement the auto-ranging function discussed above, the controller48 may essentially sweep the reference arm position along a number ofdiscrete positions that define a range that covers at least the windowof uncertainty. By way of example, if the OCT imaging system 10 isconfigured to capture an image across 2 to 3 millimeters of depth (e.g.,a “minimum depth”), each discrete position of the reference arm 40within the sweep may cover at least a different portion of the window ofuncertainty. Using the reference arm control mechanism 52, the referencearm 40 may then be adjusted to each of the discrete positions coveringthe window of uncertainty, wherein, at each discrete step, a short range(e.g., 2-3 millimeters in depth) axial scan are obtained. Once the shortrange axial scans for each discrete step is obtained, the controller 48may process these short range axial scans to determine a composite longrange scan covering the window of uncertainty.

Next, the composite scan is analyzed by the controller 48 (e.g., viaprocessor 63) to determine the region in which the sample 30 resides. Inone embodiment, the processor 63 may calculate one or more figures ofmerit (FOM) at each of the discrete reference arm positions. Based onthe FOMs, the controller 48 may determine where a maximum or minimumoccurs, which may indicate the reference arm position that is matchedwith the sample arm 32, thereby giving the position of the sample.

This process may be better understood with reference to FIG. 3, whichshows a graph illustrating an example of a composite scan 78 derivedfrom short range scans at each discrete reference arm position duringthe auto-ranging sweep along a z-axis in the reference arm 40. Forinstance, the present figure shows, by way of example, four discretereference arm positions 80 a-80 d, although other embodiments mayinclude fewer or more reference arm positions 80 depending on the depthof the window of uncertainty and/or the minimum depth that the OCTimaging system 10 is configured to capture an image. In the presentembodiment, it should be noted that adjacent reference arm positions mayslightly overlap at their boundaries 83, as indicated by referencenumber 82, although other embodiments may omit this feature.

For each short range scan (e.g., corresponding to a single reference armposition), one or more FOMs are determined. By way of example, an FOMmay include the peak intensity of the signal, the total integratedintensity of each scan, a thresholded intensity, as well as variousmeasures of sharpness similar to those used in microscopy applications,such as entropy and/or moment about a mean. Additionally, analysis offeatures unique to a sample 30, such as reflections from structuralfeatures of the sample 30, may also be a basis for deriving an FOM.Further, the analysis may include a single FOM, or a combination of FOMs(multiplied together or otherwise mathematically combined), which mayimprove accuracy. Referring still to FIG. 3, reference numbers 84represent FOM(s) determined with respect to each axial scan. By way ofexample only, the FOM 84 may be based upon reflection from structuralfeatures of the sample 30.

As shown in FIG. 3, the FOM 84 b within the portion of the compositescan 78 corresponding to the reference arm position 80 b has the highestvalue. Thus, the controller 48 may identify the reference arm position80 b as the position in which the reference arm 40 matches the samplearm 32. Accordingly, the controller 48 sends the signal 50 indicatingthe correct position to the reference arm control mechanism 52, whichmay then actuate the reference arm 40 (e.g., using a servo mechanism) tocause it to adjust to the indicated position. In other words, theanalysis of the reference arm sweep process essentially acts as afeedback loop to bring the reference arm 40 to a position that matchesthe sample arm 32 of FIG. 1. By way of example only, in one embodiment,the reference arm control mechanism 52 may include one or more rapidscanning optical delay (RSOD) lines having a grating, such as adiffraction grating, wherein the adjustments may be translated intoangular motion of either the reference mirror 38 or the grating, orboth. In additional embodiments, rather than using a control mechanism,the OCT imaging system 10 may include multiple reference arms, and theinterference signal may be distinguished using frequency encoding or byswitching between the reference arms. For instance, in such embodiments,the matching reference arm is selected from the multiple reference arms,as opposed to manipulating the path length of the reference arm. As canbe appreciated, the auto-ranging functions discussed above may generallybe performed by the processor 63 in conjunction with the auto-rangelogic 72 shown in FIG. 2.

FIG. 4 is a flowchart that illustrates the auto-ranging process 90described above with reference to FIG. 3 that may be performed by thecontroller 48 of the OCT imaging system 10 of FIG. 1. As shown, theprocess 90 begins at step 92, where an axial scan of the sample 30 isobtained at each discrete reference arm position during an auto-rangingsweep. As discussed above, the sweep is configured such that it at leastencompasses the window of uncertainty defined by variations of sampledimensions (e.g., variability in eye axial length) and/or naturalpatient variations (e.g., variations in patient face and/or headstructure).

Thereafter, at step 94, a composite scan (e.g., 78) is derived based onthe axial scans obtained at step 92. The controller 48 of the OCTimaging system 10 may then analyze the composite scan 78 to determine atleast one figure of merit (FOM) at each discrete reference arm position(e.g., 80 a-80 d), as indicated at step 96. Next, at step 98, thereference arm position that contains an FOM value that indicates thenominal position of the sample 30 is selected. For instance, theselected reference arm position may have an FOM value that is a maximum(or minimum depending on the FOM used). The selected reference armposition may match the sample arm path length at least within acoherence length, as discussed above. Finally, once the matchingreference arm position is determined, the process 90 continues to step100, and the reference arm 40 is controlled (e.g., by the controlmechanism 52) to the selected position.

III. Auto-Focusing Techniques

Before discussing the auto-focusing techniques of the present disclosurein detail, it should be noted that some conventional OCT imaging systemslack any sort of auto-focusing mechanism. As discussed above, suchconventional systems rely on manual focusing by an operator, which maybe subject to inaccuracies due at least in part to human error.Moreover, some conventional OCT imaging systems may use a low transverseresolution for a large depth-of-field, which assumes that a sample issufficiently in focus at any position in depth. However, image contrastand resolution along the depth (e.g., z-direction) are still dependentupon the position of a focusing lens relative to a sample and,therefore, it may be useful to provide a technique for automaticallydetermining an optimal focal position and bringing the focusing lens tothat position, as discussed in more detail below.

Once the reference arm 40 and the sample arm 32 are matched for OCTpurposes, the controller 48 may perform an auto-focusing function inorder to adjust the lens 28 within the sample arm 32 to a position thatprovides optimal focus with respect to the sample 30. For instance, amore detailed view of a portion of the sample arm 32 is illustrated inFIG. 5, which depicts an example in which the sample 30 is a human eye.As discussed above, OCT imaging is generally considered to beparticularly well suited to ocular diagnosis due to its ability tocapture high resolution images of layers of the retina and the cornea,as well as its non-invasiveness. For instance, OCT imaging is often usedfor early detection of various ocular diseases, such as glaucoma,diabetic retinopathy and macular degeneration (e.g., cystoid macularedema), among others.

As shown in FIG. 5, the light portion 20 provided by the beam splitter18 may be focused by the lens 28, directed to the sample 30, in thiscase an eye, and reflected as light portion 34. Whether or not thesample 30 will appear to be in focus in the resulting OCT image maydepend on the focal position of the lens 28. For instance, if the lens28 is too close or too far from the sample 30, the resulting OCT imagemay be out of focus and may not be suitable for diagnostic purposes.Accordingly, the auto-focusing process that may be performed by thecontroller 48 of the OCT imaging system 10 may determine an optimalfocal position and adjust the position of the lens 28 in the directions104 (e.g., the ±z-direction) accordingly.

The process by which the controller 48 may perform the auto-focusingprocess of the present disclosure may be similar in some aspects to theauto-ranging process described above in Section II. For instance, theauto-focusing process generally includes sweeping the lens 28 along arange of available discrete focal positions within the sample arm 32. Ateach discrete focal position, an image is acquired, and the processor 63may determine one or more quantitative figures of merit (FOM) for eachimage at each discrete focal position. For example, in one embodiment, aFOM may be a width of autocorrelation function, which may be generatedby the self-interference of light scattered from the sample only. Inthis embodiment, since the self-interference spectrum contains onlylow-frequency components, image acquisition speed may be increased bybinning some number of pixels (e.g., 2×2 binning) or by using a linescan camera with a smaller number of pixels.

In other embodiments, the FOM extracted from auto-focusing images mayinclude a mean or average image intensity, a Brenner gradient, and imageintensity (variance), to name just a few. Further, the FOM may also be acombination of two or more independent FOMs. For instance, in oneembodiment, the FOM may be the product of a Brenner gradient FOM and avariance FOM. After calculating a chosen FOM, a mathematical model isapplied to fit a function (e.g., a curve) to the FOM data with respectto focal position (depth). By way of example, the mathematical model maybe determined empirically depending upon the particular FOM of choice,as well as based upon characteristics of the focusing lens,illumination, etc. In some embodiments, the best fit may at leastpartially be determined based on any one of a number of mathematicalregression techniques. As can be appreciated, one goal may be to selecta model that uses the fewest number of fitting parameters, and therebyrequires the fewest number of images possible, which may speed up theauto-focusing process. The maximum (or minimum) of the fitted functionis taken as the optimal focal position and may be provided to the lensposition control mechanism 60 to bring the sample 30 into focus.

To provide a more illustrative example, FIGS. 6A-6I illustrate imagesacquired at various focal positions along the depth of the sample arm 32using a slice of an onion as the sample 30. For instance, FIG. 6Aillustrates an image 106 acquired at a first focal position of 0 μm,which may represent the starting position of the range along which theauto-focusing sweep of the lens 28 occurs. FIG. 6B illustrates an image108 acquired at a second focal position that is 40 μm offset from thefirst focal position. FIG. 6C illustrates an image 110 acquired at athird focal position 80 μm away from the first position. FIG. 6Dillustrates an image 112 acquired at a fourth focal position 120 μm awayfrom the first position. FIG. 6E illustrates an image 114 acquired at afifth focal position 160 μm away from the first position. FIG. 6Fillustrates an image 116 acquired at a sixth focal position 200 μm awayfrom the first position. FIG. 6G illustrates an image 118 acquired at aseventh focal position 240 μm away from the first position. FIG. 6Hillustrates an image 120 acquired at an eighth focal position 280 μmaway from the first position. Finally, FIG. 6I illustrates an image 122acquired at a third focal position 320 μm away from the first position.As can be seen, the images 106-122 are at varying degrees of focus. Inthe present example, the step size between each focal position in theauto-focus sweep is set to 40 μm. However, it should be appreciated thatthis step size may be increased or decreased in other embodiments toprovide for fewer or more images (e.g., a larger step size results inless image samples, and a smaller step size results in more imagessamples across the same sweep depth).

Next, the images 106-122 would be analyzed by the controller 48 toobtain a chosen figure of merit. For instance, a best-fit curve would bedetermined based on the FOM data with respect to focal position (depth).Referring to FIG. 7, a graph 130 is provided showing examples of severalFOM data sets and their respective fitted curves in accordance withembodiments of the present invention. For instance, curve 132 representsa mathematical model fitting FOM data based on average image intensity(mean). Curve 134 may represent a mathematical model fitting FOM databased on a Brenner gradient. By way of example, the Brenner gradient maybe determined based upon the following expression:

F _(Brenner)=Σ_(Height)Σ_(Width)((i(x+n),y)−i(x,y))²,  (1)

wherein i represents the intensity of a given pixel within an image, nrepresents a small integer (e.g., n=2), and x and y represent pixelcoordinates of the image. Generally, the Brenner gradient may, for eachpixel in a captured image, compute a difference in intensities betweeneach respective pixel and a neighboring pixel laterally separated fromthe pixel by at least one other pixel, and sum different intensities foreach pixel across the height and width of the image. Curve 136 mayrepresent a mathematical model fitting FOM data based on variance, andcurve 138 may represent a mathematical model fitting FOM data based onthe product of the Brenner gradient and variance.

Regardless of the FOM metric used, it should be understood that analysisof the fitted mathematical model is then performed to determine amaximum (or a minimum in some cases). As can be seen in FIG. 7,depending on the FOM used, a maximum occurs at between approximately175-200 micrometers. Indeed, referring back to the samples images ofFIGS. 6A-6I, the image 114 at 160 μm (FIG. 6E) and 116 at 200 μm (FIG.6F) appear to be the most in focus. The optimal focal position may thusbe determined as the position closest to the maximum (or minimum) of thefitted curve that lens 28 is capable of achieving. For instance, eventhough the step size during the auto-focus sweep may be set to 40 μm, itshould be appreciated that the lens control mechanism 60 may beconfigured to have a minimum step resolution for adjusting the lens 28at smaller intervals (e.g., 1 μm, 2 μm, 5 μm, 10 μm, etc.). On the otherhand, if the minimum step resolution of lens step size is unable toreach the exact focal position indicated by the fitted curve, thecontroller 48 may instruct the lens control mechanism 60 to position thelens 28 to the closest possible focal position, i.e. via servo control.

In another embodiment, the selected FOM may be the inverse of theBrenner gradient. As will be appreciated, a Brenner gradient functionmay be approximated using a Lorentzian function, which is given by:

$\begin{matrix}{{F(z)} = \frac{a}{\left( {z - z_{0}} \right)^{2} + b}} & (2)\end{matrix}$

As can be seen the Lorentzian function is essentially the reciprocal ofa quadratic function. Therefore, the inverse of the Brenner gradient maybe fitted using a second-order polynomial, which may be determined by asfew as three images. For instance, FIG. 8 shows a graph 140 depicting anembodiment in which the FOM used for auto-focusing is based on aninverse of the Brenner gradient. As shown here, based on FOM values 142a, 142 b, and 142 c, from three sample images, the second-orderpolynomial function 144 may be determined and fitted to the data points142 a-142 c. Accordingly, in this example, the controller 48 isconfigured to locate a minimum, as indicated by reference number 146,corresponding to the optimal focal position. As can be appreciated, insuch an example, depending on the distance of the auto-focusing sweep,it may be useful to select three focal positions that are evenlydistributed across the sweep distance so that at least one sample isobtained on either side of the optimal focal position.

FIG. 9 is a flow chart that illustrates the auto-focusing process 150described above with reference to FIGS. 5-8. The auto-focusing process150 may be performed by the controller 48 (e.g., via the processor 63and auto-focus logic 74) of the OCT imaging system 10 of FIG. 1. Asshown, the process 150 begins at step 152, wherein the lens 28 of thesample arm 32 is adjusted to each of multiple discrete focal positions,with an image of the sample 30 being obtained at each of the discretefocal positions during the auto-focus sweep in the z-direction. In theexamples provided above, the sweep may cover a focal distance or rangeof at least 300 μm or more.

Thereafter, at step 154, each of the images acquired from step 152 areanalyzed to obtain a value based on one or more figures of merit (FOMs).Next, as indicated at step 156, a mathematical model defining a curvethat best fits the FOM data points is determined. Subsequently, at step158, the fitted curve is analyzed to identify a focal position thatcorresponds to the optimal focal position. For example, depending on theFOM selected, the optimal focal position may correspond to the maximumor minimum of the fitted curve. Finally, once the optimal focal positionis determined, the process 150 continues to step 160, and the lens 28 ofthe sample arm 32 is controlled (e.g., by the lens control mechanism 60)to the selected focal position.

As will be understood, the various techniques described above andrelating auto-ranging and auto-focusing in an optical coherencetomography imaging system are provided herein by way of example only.Accordingly, it should be understood that the present disclosure shouldnot be construed as being limited to only the examples provided above.Further, it should be appreciated that the above-discussed techniquesmay be implemented in any suitable manner, including hardware (e.g.,suitably configured circuitry), software (e.g., via a computer programincluding executable code stored on one or more tangible computerreadable medium), or via using a combination of both hardware andsoftware elements. Thus, the term “code,” as used herein, may refer tomachine-readable code (e.g., readable by a computer and/or processor)that may be stored in a machine-readable storage medium (e.g., disk,hard drive, optical drive, flash memory, etc.) for execution by aprocessor.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to practice the invention, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe invention is defined by the claims, and may include other examplesthat occur to those skilled in the art. Such other examples are intendedto be within the scope of the claims if they have structural elementsthat do not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal languages of the claims.

1. An optical coherence tomography (OCT) imaging system comprising: alight source configured to emit light; a beam splitter configured to,receive the light from the light source, split the light into a firstlight portion directed along a sample arm comprising a sample and asecond light portion directed along a reference arm comprising areference mirror, receive a first reflected light portion from thesample arm and a second reflected light portion from the reference arm,and combine the first and second reflected light portions to obtain aninterference signal; and a controller comprising logic configured toperform an auto-focusing process to determine an optimal focal positionfor a lens in the sample arm in order to bring the sample into focus. 2.The OCT imaging system of claim 1, wherein the logic for performing theauto-focusing process is configured to: adjust the position of the lensto each of a plurality of focal positions, the focal positions spanninga focusing range; obtain an image of the sample at each of the focalpositions; determine a figure of merit value for each image; determine amathematical function corresponding to a best-fit curve based on thefigure of merit values; and identify the optimal focal position based onthe best-fit curve.
 3. The OCT imaging system of claim 2, comprising alens positioning control device configured to receive the optimal focalposition from the controller and to adjust the position of the lensaccording to the optimal focal position.
 4. The OCT imaging system ofclaim 3, wherein the lens positioning control system comprises amotorized actuation system.
 5. The OCT imaging system of claim 2,wherein the figure of merit value comprises a width of autocorrelationfunction, a mean image intensity value, a Brenner gradient, or avariance.
 6. The OCT imaging system of claim 5, wherein the figure ofmerit value comprises a combination of two or more types of figures ofmerits.
 7. The OCT imaging system of claim 1, wherein the light sourceis configured to emit near-infrared light.
 8. The OCT imaging system ofclaim 1, wherein the beam splitter comprises an interferometer.
 9. TheOCT imaging system of claim 1, comprising a spectral domain OCT imagingsystem, wherein the spectral domain OCT imaging comprises a spectrometerconfigured to analyze the interference signal in the spectral domain.10. A method for focusing a sample in a sample arm of an opticalcoherence tomography (OCT) imaging system comprising: acquiring an imageof the sample through a focusing lens at each of a plurality of focalpoints along a focal range in the sample arm; determining a figure ofmerit data point for each acquired image; using the figure of merit datapoints to determine a mathematical function defining a curve fitted tothe figure of merit data points; using the curve to determine an optimalfocal position; and using a lens position control device to adjust thefocusing lens to the optimal focal position.
 11. The method of claim 10,wherein the figure of merit data point comprises at least one of a widthof autocorrelation function, a mean image intensity value, a Brennergradient, a variance, or a combination thereof.
 12. The method of claim10, wherein the mathematical function is determined empirically based atleast partially upon the type of the figure of merit data point.
 13. Themethod of claim 10, wherein using the curve to determine the optimalfocal position comprises determining either a maxima or minima of thecurve, depending on the type of figure of merit data point.
 14. Themethod of claim 10, wherein the figure of merit data point comprises aninverse of a Brenner gradient.
 15. The method of claim 14, wherein thenumber of focal points comprises three focal points, and wherein themathematical function comprises a second-order polynomial.
 16. Themethod of claim 10, wherein, if a minimum step resolution of the lensposition control device is unable to reach the optimal focal point,adjusting the focusing lens to the focal point closest to the optimalfocal point that the lens position control device is able to achievebased on the minimum step resolution.
 17. The method of claim 10,wherein the focal range comprises at least 300 micrometers.
 18. Themethod of claim 10, comprising, after adjusting the focusing lens to theoptimal focal position, acquiring an OCT image by providing a firstportion of light to the sample via the sample arm, providing a secondportion of light to a reference mirror via the reference arm, combininga first reflected portion of light from the sample arm and a secondreflected portion of light from the reference arm to obtain aninterference signal, and analyzing the interference signal to generatean OCT image.
 19. A tangible computer-readable medium havinginstructions encoded thereon, wherein the instructions comprise: codeconfigured to cause a focusing lens in a sample arm of an opticalcoherence tomography (OCT) imaging system to be positioned at each of aplurality of discrete focal points along a focal range in the samplearm; code for acquiring an image of a sample in the sample arm at eachof the focal points; code for calculating a figure of merit value fromeach of the images; code for fitting a mathematical function to thefigure of merit values; code for determining an optimal focal positionbased on the mathematical function; and code to cause the focusing lensto be adjusted based upon the optimal focal position.
 20. The tangiblecomputer-readable medium of claim 19, wherein the code for determiningthe optimal focal position based on the mathematical function comprisescode for identifying a focal position corresponding to either a maximumor minimum of the mathematical function.